gridSearch: Grid search algorithm for finding the identified set

In depCensoring: Statistical Methods for Survival Data with Dependent Censoring

Grid search algorithm for finding the identified set

Description

This function implements the gridsearch and binary search algorithms used to compute the roots of the violation curve and hence in estimating the identified intervals.

Usage

gridSearch(
  dir,
  test.fun,
  hyperparams,
  evaluations = NULL,
  time.run.duration = FALSE,
  verbose = 0,
  picturose = FALSE
)

Arguments

dir	Search direction.
test.fun	The test function to be inverted in order to obtain the identified set. It should take a scalar parameter as argument (i.e. the specified value of a component of the full parameter vector) and return a list with named elements list(theta, t.stat, crit.val), where theta is the scalar value that was tested, t.stat is the value of the test statistic and crit.val is the critical value to be used in determining whether to reject or not reject.
hyperparams	List of hyperparameters.
evaluations	Matrix of already evaluated points, of which at least one is feasible. When evaluations = NULL (default), the initial feasible point search will be executed first.
time.run.duration	Boolean value indicating whether to time each step in the EAM algorithm. Requires chronometer.R. Default is time.run.duration = FALSE.
verbose	Boolean value indicating whether or not to print run time updates to the console. Default is verbose = FALSE.
picturose	Boolean value indicating whether or not to visualize the identified set search. Default is FALSE.

Value

List containing the evaluations of the test statistic and critical values, convergence information, and run times.

depCensoring documentation built on April 4, 2025, 1:52 a.m.